Hybrid Metaheuristics: An Emerging Approach to Optimization

✍ Scribed by Dr. Christian Blum, Dr. Andrea Roli (auth.), Dr. Christian Blum, Dr. Maria José Blesa Aguilera, Dr. Andrea Roli, Dr. Michael Sampels (eds.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2008
• Tongue: English
• Leaves: 293
• Series: Studies in Computational Intelligence 114
• Edition: 1
• Category: Library

✦ Synopsis

Optimization problems are of great importance in many fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. Examples of metaheuristics are simulated annealing, tabu search, evolutionary computation, iterated local search, variable neighborhood search, and ant colony optimization. In recent years it has become evident that a skilled combination of a metaheuristic with other optimization techniques, a so called hybrid metaheuristic, can provide a more efficient behavior and a higher flexibility. This is because hybrid metaheuristics combine their advantages with the complementary strengths of, for example, more classical optimization techniques such as branch and bound or dynamic programming.

The authors involved in this book are among the top researchers in their domain. The book is intended both to provide an overview of hybrid metaheuristics to novices of the field, and to provide researchers from the field with a collection of some of the most interesting recent developments.

✦ Table of Contents

Front Matter....Pages i-ix
Hybrid Metaheuristics: An Introduction....Pages 1-30
Combining (Integer) Linear Programming Techniques and Metaheuristics for Combinatorial Optimization....Pages 31-62
The Relation Between Complete and Incomplete Search....Pages 63-83
Hybridizations of Metaheuristics With Branch & Bound Derivates....Pages 85-116
Very Large-Scale Neighborhood Search: Overview and Case Studies on Coloring Problems....Pages 117-150
Hybrids of Constructive Metaheuristics and Constraint Programming: A Case Study with ACO....Pages 151-183
Hybrid Metaheuristics for Packing Problems....Pages 185-219
Hybrid Metaheuristics for Multi-objective Combinatorial Optimization....Pages 221-259
Multilevel Refinement for Combinatorial Optimisation: Boosting Metaheuristic Performance....Pages 261-289

✦ Subjects

Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics)